Brown Bag Lunch Schedule: Difference between revisions

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| '''Adil Yalçın''' <br> PhD Student, Department of Computer Science ([http://www.adilyalcin.me link])
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AggreSet: Rich and Scalable Set Exploration using Visualizations of Element Aggregations (InfoVis practice talk)
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<br> ([http://www.keshif.me/AggreSet AggreSet]) Datasets commonly include multi-value (set-typed) attributes that describe set memberships over elements, such as genres per movie or courses taken per student. Set-typed attributes describe rich relations across elements, sets, and the set intersections. Increasing the number of sets results in a combinatorial growth of relations and creates scalability challenges. Exploratory tasks (e.g. selection, comparison) have commonly been designed in separation for set-typed attributes, which reduces interface consistency. To improve on scalability and to support rich, contextual exploration of set-typed data, we present AggreSet. AggreSet creates aggregations for each data dimension: sets, set-degrees, set-pair intersections, and other attributes. It visualizes the element count per aggregate using a matrix plot for set-pair intersections, and histograms for set lists, set-degrees and other attributes. Its non-overlapping visual design is scalable to numerous and large sets. AggreSet supports selection, filtering, and comparison as core exploratory tasks. It allows analysis of set relations including subsets, disjoint sets and set intersection strength, and also features perceptual set ordering for detecting patterns in set matrices. Its interaction is designed for rich and rapid data exploration. We demonstrate results on a wide range of datasets from different domains with varying characteristics, and report on expert reviews and a case study using student enrollment and degree data with assistant deans at a major public university.
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== Past Brown Bags ==
== Past Brown Bags ==



Revision as of 18:43, 17 September 2015

The HCIL has an open, semi-organized weekly "brown bag lunch (BBL)" on every Thursdays from 12:30-1:30pm in HCIL (2105 Hornbake, South Wing). The topics range from someone's work, current interests in the HCIL, software demos/reviews, study design, proposed research topics, introductions to new people, etc. The BBL is the one hour a week where we all come together--thus, it’s a unique time for HCIL members with unique opportunities to help build collaborations, increase awareness of each other’s activities, and generally just have a bit of fun together with free food every week.

To sign up for a session, send an email to BBL student co-coordinators Austin Beck (austinbb@umd.edu) or Lelya Norooz (leylan@umd.edu). In the email, briefly describe the topic and preferred dates.

To be notified about upcoming events, please subscribe one of these mailing lists.

We thank YAHOO for its sponsorship of the HCIL Brown Bag Lunches Yahoo.jpg.

Fall 2015 Schedule

Date Leader Topic
09/03/2015 All new students!

New student introductions!


Much like last year, this BBL is for new students to introduce themselves, talk briefly about their projects and interests and bounce their ideas off the HCIL members. The purpose of these informal and participatory talks is to help connect new students with professors and other students sharing the same interests. We'll also cover useful resources for students (e.g., this very wiki!)

09/10/2015

STARTING
AT NOON
exceptionally

Jean-Daniel Fekete
Senior Research Scientist at INRIA (link)

ProgressiVis: a New Workflow Model for Scalability in Information Visualization


Information Visualization (infovis) has, for years, been limited to small data: a typical infovis application will work well with up-to 1000 items/records, a few can scale to 100,000 items, and very few, including the leading commercial products such as Tableau and Spotfire, have been able to deal with millions of items. Billions are seldom mentioned in the infovis literature. In contrast, the research fields of machine learning and databases are routinely dealing with datasets of several billions of items, and the numbers are growing.

There are legitimate reasons why it takes time for infovis to start catching-up with these large numbers, and some work such as Lins et al. Nanocubes (http://www.nanocubes.net/) and Liu et al. imMens (http://idl.cs.washington.edu/papers/immens), have started to show possible routes to scalability. However, they both rely on either pre-computed aggregations that need hours to compute for large datasets, or on a highly parallel infrastructure performing aggregations on the fly. In my talk, I will explain why we need more flexible solutions and present a new workflow architecture called ProgressiVis, to achieve progressive computations and visualization over massive datasets.

09/17/2015 Liese Zahabi
Assistant Professor of Graphic Design at the University of Maryland, College Park (link)

Exploring Information-Triage: Speculative interface tools to help college students conduct online research


In many ways, the promise of the Internet has been overshadowed by a sense of overload and anxiety for many users. The production and publication of online material has become increasingly accessible and affordable, creating a confusing glut of information users must sift through to locate exactly what they want or need. Even a fundamental Google search can often prove paralyzing.The concept of information-triage may help mitigate this issue. Information-triage is the process of sorting, grouping, categorizing, prioritizing, storing and retrieving information in order to make sense and use of it. This work examines the role of design in the online search process, connects it to the nature of human attention and the limitations of working memory, and suggests ways to support users with an information-triage system. This talk will focus on a set of three speculative online search interfaces and user-testing sessions conducted with college students to explore the possibilities for information-triage and future interface prototypes and testing.

09/24/2015 HCIL Student Presentations


10/01/2015 Celine Latulipe
Associate Professor at The University of North Carolina at Charlotte (link)


10/08/2015 Adil Yalçın
PhD Student, Department of Computer Science (link)

AggreSet: Rich and Scalable Set Exploration using Visualizations of Element Aggregations (InfoVis practice talk)


(AggreSet) Datasets commonly include multi-value (set-typed) attributes that describe set memberships over elements, such as genres per movie or courses taken per student. Set-typed attributes describe rich relations across elements, sets, and the set intersections. Increasing the number of sets results in a combinatorial growth of relations and creates scalability challenges. Exploratory tasks (e.g. selection, comparison) have commonly been designed in separation for set-typed attributes, which reduces interface consistency. To improve on scalability and to support rich, contextual exploration of set-typed data, we present AggreSet. AggreSet creates aggregations for each data dimension: sets, set-degrees, set-pair intersections, and other attributes. It visualizes the element count per aggregate using a matrix plot for set-pair intersections, and histograms for set lists, set-degrees and other attributes. Its non-overlapping visual design is scalable to numerous and large sets. AggreSet supports selection, filtering, and comparison as core exploratory tasks. It allows analysis of set relations including subsets, disjoint sets and set intersection strength, and also features perceptual set ordering for detecting patterns in set matrices. Its interaction is designed for rich and rapid data exploration. We demonstrate results on a wide range of datasets from different domains with varying characteristics, and report on expert reviews and a case study using student enrollment and degree data with assistant deans at a major public university.

10/15/2015


10/22/2015 Heather Bradbury
Director, Masters of Professional Studies Programs at Maryland Institute College of Art (link)


10/29/2015 Kurt Luther
Assistant Professor of Computer Science in HCI/CSCW at Virginia Tech (link)


11/05/2015 C. Scott Dempwolf
Research Assistant Professor and Director, UMD - Morgan State Joint Center for Economic Development (link)


11/12/2015


11/19/2015


11/26/2014 No Brown Bag for Thanksgiving break.
12/03/2015


12/10/2015


12/17/2015



Past Brown Bags

View the Past Brown Bag Lunch Schedules to learn more about prior talks.